How are the number of neurons in the output layers chosen?

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Precious Eze
Precious Eze el 16 de Sept. de 2017
Respondida: Osama Tabbakh el 1 de Mayo de 2019
I discovered that after choosing the number of neurons in the hidden layer, the network automatically sets the number of output neurons. Whats the intuition behind it?
  2 comentarios
Osama Tabbakh
Osama Tabbakh el 7 de Abr. de 2019
I have the same question but obviously nobody has answer.
Greg Heath
Greg Heath el 9 de Abr. de 2019
???
My answer ( O ) was given ~ 1.5 years ago
Greg

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Respuestas (2)

Greg Heath
Greg Heath el 17 de Sept. de 2017
[ I N ] = size(input)
[ O N ] = size(target)
I-H-O = size of a single layer NN
You (lucky dog) have the extreme pleasure of either
setting H OR accepting the default H=10.
Hope this helps.
Thank you for accepting my exceptional answer
Greg

Osama Tabbakh
Osama Tabbakh el 1 de Mayo de 2019
I discovered why Matlab does that. I will explain it.
Matlab tried to make the samples easier to train, that why he deletes the values of the vector, which are either zero or not important to train. But you get at the end, what you would have.
In the attachment, you see that I have in the output vector 60 components but the last 20 are just zeros, what why he deletes them from the output layer and put it back in the output.

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